Evidence map›Paper›PMID 35749466›Full record

ArticlePloS one2022

Understanding 'monitoring' data-the association between measured stressors and athlete responses within a holistic basketball performance framework.

Richard A J Mercer, Jennifer L Russell, Lauren C McGuigan, Aaron J Coutts, Donnie S Strack, Blake D McLean

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.2field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 14 citations in OpenAlex.

  1. Trial
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  6. Sports Diagnostics-Maximizing the Results or Preventing Injuries.International journal of environmental research and public health · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 2 countries.

Richard A J MercerFaculty of Health, School of Sport, Exercise and Rehabilitation, University of Technology Sydney (UTS), Sydney, NSW, Australia.ORCID 0000-0001-7975-6721
Jennifer L RussellFaculty of Health, School of Sport, Exercise and Rehabilitation, University of Technology Sydney (UTS), Sydney, NSW, Australia.
Lauren C McGuiganFaculty of Health, School of Sport, Exercise and Rehabilitation, University of Technology Sydney (UTS), Sydney, NSW, Australia.
Aaron J CouttsFaculty of Health, School of Sport, Exercise and Rehabilitation, University of Technology Sydney (UTS), Sydney, NSW, Australia.
Donnie S StrackHuman and Player Performance, Oklahoma City Thunder Professional Basketball Club, Oklahoma City, Oklahoma, United States of America.
Blake D McLeanFaculty of Health, School of Sport, Exercise and Rehabilitation, University of Technology Sydney (UTS), Sydney, NSW, Australia.ORCID 0000-0003-1966-8716
University of Technology Sydney · AUNational Wheelchair Basketball Association · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study examined associations between cumulative training load, travel demands and recovery days with athlete-reported outcome measures (AROMs) and countermovement jump (CMJ) performance in professional basketball. Retrospective analysis was performed on data collected from 23 players (mean±SD: age = 24.7±2.5 years, height = 198.3±7.6 cm, body mass = 98.1±9.0 kg, wingspan = 206.8±8.4 cm) from 2018-2020 in the National Basketball Association G-League. Linear mixed models were used to describe variation in AROMs and CMJ data in relation to cumulative training load (previous 3- and 10-days), hours travelled (previous 3- and 10-day), days away from the team's home city, recovery days (i.e., no travel/minimal on-court activity) and individual factors (e.g., age, fatigue, soreness). Cumulative 3-day training load had negative associations with fatigue, soreness, and sleep, while increased recovery days were associated with improved soreness scores. Increases in hours travelled and days spent away from home over 10 days were associated with increased sleep quality and duration. Cumulative training load over 3 and 10 days, hours travelled and days away from home city were all associated with changes in CMJ performance during the eccentric phase. The interaction of on-court and travel related stressors combined with individual factors is complex, meaning that multiple athletes response measures are needed to understand fatigue and recovery cycles. Our findings support the utility of the response measures presented (i.e., CMJ and AROMs), but this is not an exhaustive battery and practitioners should consider what measures may best inform training periodization within the context of their environment/sport.

Indexed as

Athletic PerformanceBasketballAdultAthletesFatigueHumansRetrospective StudiesTravelTravel-Related IllnessYoung Adult

Identifiers

PMID35749466
PMCPMC9231705
OpenAlexW4283398655

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.